Snort acoustic structure codes for positive emotions in horses

Abstract : While the vocal coding of human and animal internal states has been widely studied, the possible acoustic expression of “positive” emotions remains poorly known. Recent studies suggest that snorts (non-vocal sounds produced by the air expiration through the nostrils) appear to be reliable indicators of positive internal states in several ungulate species. Here, we hypothesised in horses that the acoustic structure of the snort could vary with the subjects’ current emotional state. Indeed, a preliminary sound analysis of snorts let us suggest structure variations related to the presence of pulsations. We recorded snorts from 20 horses living in a riding center. Auditory playbacks run with 20 humans first confirmed the existence of two snort subtypes, i.e. one pulsed and one non-pulsed. Observations were then conducted to compare the distribution of these two subtypes according to the location (stall/pasture) of the signaller as a contextual determinant of its internal state and to its ears’ position as a reflection of its emotional state. We found that both subtypes were preferentially observed in positive contexts, but that pulsed snorts were even more associated with highly appreciated situations (in pasture and with ears forward). This study is a step further in the identification of indicators of positive emotions in horses and more generally in the understanding of the acoustic emotions’ coding.
Complete list of metadatas

https://hal-univ-rennes1.archives-ouvertes.fr/hal-01892070
Contributor : Antoine L'Azou <>
Submitted on : Wednesday, October 10, 2018 - 12:03:09 PM
Last modification on : Wednesday, July 31, 2019 - 4:54:15 PM

Identifiers

Citation

Mathilde Stomp, Maël Leroux, Marjorie Cellier, Séverine Henry, Martine Hausberger, et al.. Snort acoustic structure codes for positive emotions in horses. The Science of Nature Naturwissenschaften, Springer Verlag, 2018, 105 (9-10), pp.57. ⟨10.1007/s00114-018-1582-9⟩. ⟨hal-01892070⟩

Share

Metrics

Record views

80